AI Patient Identification Using SDOH for Clinical Trial Diversity
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Solution Overview
Problem
Clinical trials face enrollment delays due to lack of awareness among patients and healthcare providers, insufficient diversity in participant demographics, and inadequate targeting strategies, leading to delayed therapy approvals and potentially irrelevant trial results.
Innovation Solution
An AI-assisted system that uses social determinants of health (SDOH) factors to identify and recruit patients for clinical trials by analyzing patient medical records, determining demographic profiles, and communicating candidate identities to healthcare providers through a networked portal or asynchronous communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual patient screening methods are used, then healthcare providers can identify clinical trial candidates, but the process is time-consuming and results in significant enrollment delays
Solution Approach 1:
The patent replaces manual mechanical screening processes with an automated computer-based system that uses artificial intelligence and machine learning algorithms to analyze medical records, patient demographics, and clinical trial criteria, dramatically increasing screening speed and reducing enrollment delays
Solution Approach 2:
The patent introduces a computer-based intermediary system that acts as a mediator between clinical trial databases and patient medical records, automatically matching candidates to appropriate trials based on predefined criteria and reducing the time burden on healthcare providers
2Quantity of substance
If patient screening is limited to facilities where research is conducted, then some candidates can be identified, but the majority of potentially eligible patients in community care centers are missed
Solution Approach 1:
The patent creates a universal screening system that can access and analyze patient data from multiple healthcare settings including community care centers, specialty clinics, and research facilities through standardized electronic health record interfaces, expanding the reach beyond single-facility limitations
Solution Approach 2:
The patent expands the screening capability from a single-facility dimension to a multi-facility network dimension by implementing a distributed system that queries multiple healthcare provider databases simultaneously, dramatically increasing the pool of identifiable candidates
3Adaptability or versatility
If diverse demographic targeting strategies are implemented, then trial participant diversity can be improved, but the system complexity and data requirements increase
Solution Approach 1:
The patent utilizes changes in demographic parameters and social determinants of health data to identify and recruit diverse patient populations, allowing the system to adapt screening criteria based on the specific needs of different demographic groups while maintaining manageable system complexity through standardized data collection protocols
Data Source
AI summary
A method includes obtaining patient medical record information from a plurality of providers until a demographic profile of patients associated with the patient medical record information meets a desired demographic profile; querying the patient medical record information using selection criteria to identify a first subset of patients having first characteristics that match first screening requirements for a clinical trial; identifying, using an artificial intelligence engine, ones of the first subset of patients whose medical record information includes second characteristics that match second screening requirements for the clinical trial as clinical trial patient candidates; and communicating identities of the clinical trial patient candidates to ones of the plurality of providers that provide healthcare services to the clinical trial patient candidates, respectively. The plurality of providers are associated with a plurality of different organizational managing entities, respectively.